Murilo Coelho Naldi

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Dealing with big amounts of data is one of the challenges for clustering, which causes the need for distribution of large data sets in separate repositories. However, most clustering techniques require the data to be centralized. One of them, the k-means, has been elected one of the most influential data mining algorithms. Although exact distributed(More)
Dealing with big amounts of data is one of the challenges for clustering, which causes the need for distribution and management of huge data sets in separate repositories. New distributed systems have been designed to scale up from a single server to thousands of machines. The MapReduce framework allows to divide a job and combine the results seamlessly.(More)
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